Papers by Bingqian Lin

3 papers
Structured Preference Optimization for Vision-Language Long-Horizon Task Planning (2025.emnlp-main)

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Challenge: Existing vision-language planning methods struggle with long-horizon reasoning in dynamic environments due to the difficulty of training models to generate high-quality reasoning processes.
Approach: They propose a framework that enhances reasoning and action selection for long-horizon task planning through structured evaluation and optimized training.
Outcome: The proposed framework outperforms existing methods on short-horizon tasks but struggles with long-horizon reasoning in dynamic environments.
MapGPT: Map-Guided Prompting with Adaptive Path Planning for Vision-and-Language Navigation (2024.acl-long)

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Challenge: Embodied agents equipped with GPT as their brains have extraordinary decision-making and generalization abilities across various tasks.
Approach: They propose a map-based agent that introduces an online linguistic-formed map to encourage global exploration.
Outcome: The proposed agent achieves state-of-the-art zero-shot performance on R2R and REVERIE simultaneously.
RelCLIP: Adapting Language-Image Pretraining for Visual Relationship Detection via Relational Contrastive Learning (2022.emnlp-main)

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Challenge: Existing visual relationship detection models only use numeric ids of relation labels for training, but ignore semantic correlation between labels.
Approach: They propose a visual Relationship prediction framework that transfers natural language knowledge from Contrastive Language-Image Pre-training models to enhance the relationship prediction.
Outcome: The proposed framework improves visual relationship prediction by matching semantic correlations with relation triplets.

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